Towards a new "stromal-based" classification system for human breast cancer prognosis and therapy

Agnieszka K. Witkiewicz, Mathew C. Casimiro, Abhijit Dasgupta, Isabelle Mercier, Chenguang Wang, Gloria Bonuccelli, Jean François Jasmin, Philippe G. Frank, Richard G. Pestell, Celina G. Kleer, Federica Sotgia, Michael P. Lisanti

Research output: Contribution to journalReview articlepeer-review

54 Scopus citations

Abstract

Here, we discuss recent evidence that an absence of stromal Cav-1 expression in human breast cancers is a powerful single independent predictor of early disease recurrence, metastasis and poor clinical outcome. These findings have now been validated in two independent patient populations. Importantly, the predictive value of stromal Cav-1 is independent of epithelial marker status, making stromal Cav-1 a new "universal" or "widely- applicable" breast cancer prognostic marker. We propose based on the expression of stromal Cav-1, that breast cancer patients could be stratified into high-risk and low-risk groups. High-risk patients showing an absence of stromal Cav-1 should be offered more aggressive therapies, such as anti-angiogenic approaches, in addition to the standard therapy regimens. Mechanistically, loss of stromal Cav-1 is a surrogate biomarker for increased cell cycle progression, growth factor secretion, "stemness", and angiogenic potential in the tumor microenvironment. Since almost all cancers develop within the context of a stromal microenvironment, this new stromal classification system may be broadly applicable to other epithelial and non-epithelial cancer subtypes, as well as "pre-malignant" lesions (carcinoma in situ).

Original languageEnglish (US)
Pages (from-to)1654-1658
Number of pages5
JournalCell Cycle
Volume8
Issue number11
DOIs
StatePublished - Jun 1 2009

Keywords

  • Biomarkers
  • Breast cancer
  • Cancer-associated fibroblasts
  • Caveolin-1
  • Prognosis
  • Stroma
  • Treatment stratification

ASJC Scopus subject areas

  • Molecular Biology
  • Developmental Biology
  • Cell Biology

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